pv capacity methodologies

Moving Toward Consensus on a Photovoltaic Generation Capacity Valuation Methodology

Richard Perez State University of New York at AlbanyMike Taylor Solar Electric Power AssociationTom Hoff Clean Power ResearchJP Ross Vote Solar

OBJECTIVE

The U.S. Department of Energy’s Solar America Initiative has provided funding to evaluate the variety of photovoltaic capacity valuation methods and to bring the solar industry, electric utility, and research communities together with the goal of consensus on the most appropriate PV generation capacity valuation methodology.

LOAD

PV

At Issue: Quantifying PV Capacity Credit

Perez, Taylor, Hoff & Ross

There are three operational definitions that need to be distinguished that are an important part of the present discussion.

1. A method is a specific mathematical model (formula) for calculating a PV capacity value.

2. Each method may have different input variables, such as electric system demand, PV capacity and performance, time parameters, number of installations, geography, and/or back-up/storage.

3. The sampling interval of the input variables can be adjusted according to utility, regulatory, or other preferences

There are three operational definitions that need to be distinguished that are an important part of the present discussion.

1. A method is a specific mathematical model (formula) for calculating a PV capacity value.

2. Each method may have different input variables, such as electric system demand, PV capacity and performance, time parameters, number of installations, geography, and/or back-up/storage.

3. The sampling interval of the input variables can be adjusted according to utility, regulatory, or other preferences

We assembled a catalogue of 8 methodologies

ELCC Effective load carrying CapabilityLDMC Load Duration Magnitude CapacityLDTC Load Duration Time CapacitySLC Solar Load Control CapacityMBESC Minimum Buffer Energy Storage capacityTSW Time-Season-WindowCF Capacity FactorDTIM Day-Time Interval matching

LOAD


X MW PV

LOAD NEW LOAD


Load increase, constant LOLP

X MW PV

LOAD NEW LOAD


Y MW = ELCC

Load increase, constant LOLP

X MW PV

%ELCC = Y / X

LOAD NEW LOAD


1,000

1,100

1,200

1,300

1,400

1,500

1,600

Top of the load duration curve

load

(MW

)

load duration without PV

load duration with PV at 20% penetration

Load duration with ELCC capacity installed


40%

50%

60%

70%

80%

90%

100%

p

8760 hours

LDMC = average relative PV output for these points


LDMC


40%

50%

60%

70%

80%

90%

100%

p

8760 hours



40%

50%

60%

70%

80%

90%

100%

0% 20% 40% 60% 80%

p’

LDTC = average relative PV output for these points

LDTC = average relative PV output for these points

LDMC

LDTC


1000

1100

1200

1300

1400

1500

1600

500 sorted highest loads

load

(MW

)

X = Installed PV

L

Load duration curve

Load duration curve with PV

Upper section of load duration curve

Solar-Load-Control-based Capacity

SLC


1000

1100

1200

1300

1400

1500

1600


load

(MW

)

X = Installed PV

L

Load duration curve


SLC: demand response needed to achieve peak demand reduction = X



SLC%SLC = (X-Y) / X


1000

1100

1200

1300

1400

1500

1600


load

(MW

)

X = Installed PV

LY

Load duration curve



Same amount of demand response, but applied without PV



SLC


1000

1100

1200

1300

1400

1500

1600


load

(MW

)

X = Installed PV

LY

Load duration curve



Same amount of demand response, but applied without PV


Effective capacity = X - Y


SLC%SLC = (X-Y) / X


0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD

Peak reductionthresholdPV output

NominalPV output W/kW-ptc

oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

MBESC


Installed PV capacity

x

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

MBESC



x

Minimum Buffer Energy Storage (MBES)

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

MBESC



x


Same storage applied without PV

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

MBESC



x


Same storage applied without PV

Achieved peak reduction with MBES, but w/o PV

Y’

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

Achieved peak reduction with MBES, but w/o PV


0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

0

500

1000

1500

2000

2500

3000

Time of Day

Load

(MW

)

0

200

400

600

800

1000

1200

1400

1600

1800

2000Load - PV

LOAD



oo

x Y’


Same storage applied without PVEffective capacity = X – Y’

MBESC

%MBESC = (X-Y’) / X


TSW


TSW


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 11 21 31 41 51

% rated PV output

HORIZONTAL PV

0% 20% 40% 60% 80% 100%

Probability

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 11 21 31 41 51

% rated PV output

HORIZONTAL PV

0% 20% 40% 60% 80% 100%

Probability

Capacity credit

TSW


Average OutputInstalled Capacity%CF =


DTIM

Sampling interval a few secondsDispatch cycle several sampling intervalsEvaluation period day/time window

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

7:30 8:30 9:30 10:30 11:30 12:30 13:30 14:30 15:30 16:30 17:30

Ten Second Period Ending

Cha

nge

in %

of F

ull O

utpu

t

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Tota

l Gen

erat

ion

in M

W

PV Power generation

10 seconds variability

Maximum PV outputMaxSolarPowerDC defines best solar output capacity

Minimum PV outputMinSolarPowerDC defines least solar output capacity

Three time references

Perez, Taylor, Hoff & Ross Source: T. HANSEN


LOA

D

load duration without PVload duration with PV

X = installed PV Capacity≈ MaxSolarPowerDC

Load Duration Curves with Time Resolution Equal to Dispatch Sampling Interval

DTIM

Perez, Taylor, Hoff & RossPerez, Taylor, Hoff & Ross Source: T. HANSEN


LOA

D

load duration without PVload duration with PV

Top of LD curve w/o PV

Top of LD curve with PV

X = installed PV Capacity≈ MaxSolarPowerDC

Z = difference between tops of LD curves ≈ MinSolarPowerDC

Capacity Credit

%DTIM = Z/X

Load Duration Curves with Time Resolution Equal to Dispatch Sampling Interval

DTIM

Perez, Taylor, Hoff & RossPerez, Taylor, Hoff & Ross Source: T. HANSEN

Rochester Gas & Electric

Nevada Power

Portland General

• 3 utilities

• Hourly Load and PV generation data for 2003

• PV capacity penetration from 1% to 20%


NEVADA POWER


0%

20%

40%

60%

80%

100%

0% 5% 10% 15% 20%

Grid penetration

Effe

ctiv

e C

apac

ityELCC LDMCLDTC SLCMBESC TSWpeakTSWtime CFDTIM

PORTLAND GENERAL


0%

20%

40%

60%

80%

100%

0% 5% 10% 15% 20%

Grid penetration

Effe

ctiv

e C

apac

ityELCCLDMCLDTCSLCMBESCTSWpeakTSWtimeCFDTIM

0%

20%

40%

60%

80%

100%

0% 5% 10% 15% 20%

Grid penetration

Effe

ctiv

e C

apac


ROCHESTER GAS & ELECTRIC


0%

20%

40%

60%

80%

100%

0% 5% 10% 15% 20%

Grid penetration

Effe

ctiv

e C

apac


ROCHESTER GAS & ELECTRIC

General agreement between most metrics based upon a physical definition of capacity


Springerville

Demand-Time Interval Matching (DTIM)

4.6 MW Springerville PV Plant Actual Production Data

Tucson Electric Power


Springerville

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

7:30 8:30 9:30 10:30 11:30 12:30 13:30 14:30 15:30 16:30 17:30


Cha

nge

in %

of F

ull O

utpu

t

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Tota

l Gen

erat

ion

in M

W





Springerville

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

7:30 8:30 9:30 10:30 11:30 12:30 13:30 14:30 15:30 16:30 17:30


Cha

nge

in %

of F

ull O

utpu

t

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Tota

l Gen

erat

ion

in M

W




Capacity credit


Stakeholders WorkshopSolarPower 2007, Long Beach, CA, 9/27/07


40 participants almost 50% from utilities



FOCUS ON METHODOLOGY

Is deterministic (rather than statistical)

Provides operational measure of firm capacity when back-up/storage is available

Can be used to perform worst case analysis and addresses short term variability issues

Based on load duration curve

Accounts for effect over all hours

Accounts for PV penetration

Based on actual PV output/load correlation

SUBSTANCEHas been implemented by utilities

*Produces results that are consistent with other metrics that account for PV penetration

Based on concepts familiar to utilities

Simple to describe

Simple to implement

PROCESS

DTIM

CFTSW (peak/time)

SLCMBESCLDTC LDMCELCCImportance

MethodsAttributes











Simple to describe

Simple to implement

PROCESS

DTIM

CFTSW (peak/time)


MethodsAttributes











Simple to describe

Simple to implement

PROCESS

DTIM

CFTSW (peak/time)


MethodsAttributes











Simple to describe

Simple to implement

PROCESS

DTIM

CFTSW (peak/time)


MethodsAttributes











Simple to describe

Simple to implement

PROCESS

DTIM

CFTSW (peak/time)


MethodsAttributes











Simple to describe

Simple to implement

PROCESS

DTIM

CFTSW (peak/time)


MethodsAttributes

WORKSHOP QUESTIONS

Methods

• Are there clarifying questions about the methods presented?• Are there methods that should be included but are missing?• Are there attributes that should be included but are missing?• What level of important should be assigned to the various attributes?

Narrowing the Methods

• What methods have clear weaknesses and should not be considered?• What are the strengths or weaknesses of the remaining methods, recognizing the diversity of load profiles, reliability criteria and other generation resource differences across utilities?• Are there methods that have clear advantages?• Is there one method that can be most practically utilized by utilities to calculate PV capacity accurately and appropriately?



FOCUS ON METHODOLOGYGeographyTime scale

WORKSHOP QUESTIONS

Geographical Dispersion and Sample Intervals

• Under what conditions should different time sampling intervals (10 second, 1 hour, etc) be utilized? What time sampling intervals are used within other utility operations?• Under what conditions should or shouldn’t multiple installations over distances be utilized?• How do different time and geography sampling intervals address different concerns? (short time over wide geography, or vice versa)• How important is a back-up/storage input variable as a component of a capacity method?

Methods in Practice• How can the best method or methods be implemented in actual practice within the utility environment?• As individual utility control areas experience high PV penetration, should• reliability criteria be evaluated over multiple control areas?




Input data and logistics

WORKSHOP QUESTIONS

Data Logistics

• If the appropriate time-interval is available, is satellite modeled data acceptable? Under what conditions?• If appropriate satellite data is unavailable, are reference site proxies acceptable? Under what conditions?• What contingency plans could be utilized for new installations with no operational history?• For what sizes or types of systems is high-quality on-site monitoring necessary to collect short time-intervals versus proxy data from reference locations?




Input data and logisticsValue of capacity (who pays for it and how)Cost of PVOwnership of PVVery high penetration of PVPV alone, vs. synergy with storage and controlsRigorous LOLP simulation

FOCUS ON METHODOLOGY

STRAW POLL• Load duration methods• ELCC• MBES-SLC• DTIM• Time-Season-windows• Capacity Factor

0

5

10

15

20

25

LDMETHODS

ELCC SLC /MBES

DTIM TSW CF

IndustryGovernmentUtilitiesALL

GeographyTime scale

Continued discussion with stakeholdersvia workshops and publications

0

5

10

15

20

25

LDMETHODS

ELCC SLC /MBES

DTIM TSW CF

IndustryGovernmentUtilitiesALL

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